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CountSmall() is not a valid statistical function in TIBCO Spotfire. It is not listed among the statistical functions that can be used in expressions or data functions. The other options are valid statistical functions that can perform calculations such as counting non-empty values, computing the lower adjacent value, or calculating the standard deviation. References: Statistical Functions - TIBCO Software

 A data function is a reusable calculation that can be applied to data in a Spotfire analysis. A data function can have input and output parameters that define how the data function interacts with the data and the analysis. The input parameters specify what data or values are required for the data function to run, and the output parameters specify what data or values are returned by the data function. The types of input or output parameters for a data function are1:

Column: A column parameter represents a single column of data from a data table. A column parameter can be used as input to provide a vector of values to the data function, or as output to create a new column in the data table or overwrite an existing column. A column parameter can have a data type such as real, integer, string, or boolean.

Document property: A document property parameter represents a value that is stored in the analysis document and can be used to control various aspects of the analysis, such as filters, markings, colors, etc. A document property parameter can be used asinput to provide a scalar value to the data function, or as output to create a new document property or overwrite an existing document property. A document property parameter can have a data type such as real, integer, string, boolean, date, or time.

Value: A value parameter represents a scalar value that is entered by the user or calculated by the data function. A value parameter can be used as input to provide a constant or variable value to the data function, or as output to return a single value from the data function. A value parameter can have a data type such as real, integer, string, boolean, date, or time.

The other options, column property, table, and visualization, are not valid types of input or output parameters for a data function. References:

Details on Data Functions – Parameters

Configuring Data Function Parameters

How to select/deselect inputs/outputs/parameters in Statistica Data Function for Spotfire

How to pass input from Spotfire to Statistica Data Function?

TIBCO Streaming is a product family that combines the features of TIBCO StreamBase and TIBCO LiveView (formerly Live Datamart). TIBCO StreamBase Studio is a powerful Eclipse-based IDE that allows developers to create, test, and deploy streaming applications using a graphical language called EventFlow. TIBCO LiveView Server is a component that enables continuous querying and live data visualization for streaming data. TIBCO StreamBase Server is the core engine that executes streaming applications and provides high performance, scalability, and fault tolerance. TIBCO Spotfire Server is not part of TIBCO Streaming, but it can integrate with TIBCO Spotfire Data Streams, which is a Spotfire add-on product that uses the same technology as TIBCO LiveView Server. References: TIBCO Streaming Information, TIBCO Streaming | TIBCO Access Point, Community Product: TIBCO Streaming

Action controls are components that can be added to a text area to perform various actions when clicked. They can be either links, buttons, or images. The actions can include opening TIBCO Spotfire tools, applying bookmarks, navigating to a certain page or visualization, executing scripts, or refreshing data functions1. Scripts are custom actions that use the IronPython scripting functionality to automate tasks or extend the functionality of Spotfire2. Images are not a type of action control, but they can be used as the appearance of an action control1. References: Details on Action Control, IronPython Scripting in TIBCO Spotfire

 The R language is a dialect of S, which was designed in the 1980s and has been in widespread use in the statistical community since. The R language provides, among other things, a programming language, high level graphics, interfaces to other languages and debugging facilities. The R language is an open-source software, which means it is freely available to anyone. It can be accessed by a vibrant community of users and developers. The R language is an implementation of the S programming language. It also combines with lexical scoping semantics inspired by Scheme. The project was conceived in 1992, with an initial version released in 1995 and a stable beta version in 2000123. References: R Programming Language - Introduction, R Language Definition, R (programming language) - Wikipedia

 Data functions are scripts that can perform any type of calculation and return the results to an analysis. They can be created using R, Python, or other languages, and they can take input from data tables, columns, or properties, and output data tables, columns, or properties. Data functions can be executed on demand, automatically, or triggered by markings or filters. Data functions can be added to an analysis using the Tools > Register Data Functions menu option in the Spotfire Analyst client, or using the Add Data Function option in the Spotfire Server web interface. References: What are data functions?, Spotfire Data Function Library: Python and R Scripts for Data Analysis, Linear Regression in R | A Step-by-Step Guide & Examples

 A pivot transformation is one way to transform data from a tall/skinny format to a short/wide format. The data is distributed into columns, usually aggregating the values. This means that multiple values from the original data end up in the same place in the new data table. A pivot transformation requires selecting row identifiers, column titles, values and aggregation methods, and optionally transfer columns and aggregation methods12. The function of the pivot transformation is to pivot row values into columns of data, based on the chosen parameters34. References:

Pivoting Data - TIBCO Software

Details on Pivot Data - TIBCO Software

Transforming Data - TIBCO Software

Transforming Data - TIBCO Software

Correlation similarity is a distance measure option of the line similarity tool that calculates the similarity value by comparing the shape of a line to the master line selected. Correlation similarity measures how well the values of two lines are linearly related, regardless of their absolute values or offsets. A high correlation similarity means that the lines have similar shapes,while a low correlation similarity means that the lines have different shapes or opposite directions. Correlation similarity is useful when the absolute values or scales of the lines are not important, but the relative trends or patterns are. References: Details on Line Similarity, How to Perform a Line Similarity Comparison